MOUSE2: Molecular Ordering Utilities for Simulations, Edition 2




molecular simulation, polymers, helicity, simulation data processing, order parameters, performance optimization


The progress in spatial and temporal scales of molecular simulations attainable with modern supercomputers makes the processing of the simulation data a challenging task in itself. One of the most important applications is simulation of living systems, which are based on polymers, as well as simulation of polymer systems in material sciences. The behavior of many polymer systems is determined by the local ordering of polymer chains, which on many occasions contain helical motifs. This ordering can be hard to quantify visually and using standard tools. To overcome these problems, we have developed an original toolkit to look into orientational and especially chiral ordering in polymer systems, which can quantify the orientational ordering of polymers based on their spatial proximity as well as assess the stiffness, helical and superhelical ordering based on polymer connectivity. The proposed software is aimed at balancing the flexibility and computational efficiency. The quantitative order parameters can be useful to quantify various types of self-organization observed in coarse-grained as well as all-atom particle simulations. The utilities can be tailored to meet specific user requirements.


Abraham, M.J., Murtola, T., Schulz, R., et al.: GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers. SoftwareX 1-2, 19–25 (Sep 2015).

Abramova, A., Glagolev, M., Vasilevskaya, V.: Structured globules with twisted arrangement of helical blocks: Computer simulation. Polymer 253, 124974 (Jun 2022).

Adamcik, J., Mezzenga, R.: Amyloid Polymorphism in the Protein Folding and Aggregation Energy Landscape. Angewandte Chemie International Edition 57(28), 8370–8382 (Jul 2018).

Allen, M.P., Tildesley, D.J.: Computer simulation of liquids. Oxford University Press, Oxford, United Kingdom, second edition edn. (2017)

Arora, A., Morse, D.C., Bates, F.S., Dorfman, K.D.: Commensurability and finite size effects in lattice simulations of diblock copolymers. Soft Matter 11(24), 4862–4867 (2015).

Baldwin, R.L., Rose, G.D.: Is protein folding hierarchic? II. Folding intermediates and transition states. Trends in Biochemical Sciences 24(2), 77–83 (Feb 1999).

Baldwin, R.L., Rose, G.D.: Is protein folding hierarchic? II. Folding intermediates and transition states. Trends in Biochemical Sciences 24(2), 77–83 (Feb 1999).

Bates, F.S., Fredrickson, G.H.: Block Copolymer Thermodynamics: Theory and Experiment. Annual Review of Physical Chemistry 41(1), 525–557 (Oct 1990).

Berman, H.M., Westbrook, J., Feng, Z., et al.: The Protein Data Bank. Nucleic Acids Research 28(1), 235–242 (01 2000).

Brehm, M., Thomas, M., Gehrke, S., Kirchner, B.: TRAVIS—A free analyzer for trajectories from molecular simulation. The Journal of Chemical Physics 152(16), 164105 (Apr 2020).

Cajamarca, L., Grason, G.M.: Geometry of flexible filament cohesion: Better contact through twist? The Journal of Chemical Physics 141(17), 174904 (Nov 2014).

Cejas, M.A., Kinney, W.A., Chen, C., et al.: Thrombogenic collagen-mimetic peptides: Self-assembly of triple helix-based fibrils driven by hydrophobic interactions. Proceedings of the National Academy of Sciences 105(25), 8513–8518 (Jun 2008).

Chaudhuri, D., Mulder, B.M.: Spontaneous Helicity of a Polymer with Side Loops Confined to a Cylinder. Physical Review Letters 108(26), 268305 (Jun 2012).

Chen, J.T., Thomas, E.L., Ober, C.K., Mao, G.P.: Self-Assembled Smectic Phases in Rod-Coil Block Copolymers. Science 273(5273), 343–346 (Jul 1996).

Claessens, M.M.A.E., Semmrich, C., Ramos, L., Bausch, A.R.: Helical twist controls the thickness of F-actin bundles. Proceedings of the National Academy of Sciences 105(26), 8819–8822 (Jul 2008).

Ermilov, V.A., Vasilevskaya, V.V., Khokhlov, A.R.: Secondary globular structure of copolymers containing amphiphilic and hydrophilic units: Computer simulation analysis. Polymer Science Series A 49(1), 89–96 (Jan 2007).

Frenkel, D.: Simulations: The dark side. The European Physical Journal Plus 128(1), 10 (Jan 2013).

Gartner, T.E., Jayaraman, A.: Modeling and Simulations of Polymers: A Roadmap. Macromolecules 52(3), 755–786 (Feb 2019).

Glagolev, M.K., Glagoleva, A.A., Vasilevskaya, V.V.: Microphase separation in helix-coil block copolymer melts: computer simulation. Soft Matter 17(36), 8331–8342 (2021).

Glagolev, M.K., Vasilevskaya, V.V.: Liquid-Crystalline Ordering of Filaments Formed by Bidisperse Amphiphilic Macromolecules. Polymer Science, Series C 60(1), 39–47 (Sep 2018).

Glagolev, M.K., Vasilevskaya, V.V., Khokhlov, A.R.: Compactization of rigid-chain amphiphilic macromolecules with local helical structure. Polymer Science Series A 52(7), 761–774 (Jul 2010).

Glagolev, M.K., Vasilevskaya, V.V., Khokhlov, A.R.: Formation of fibrillar aggregates in concentrated solutions of rigid-chain amphiphilic macromolecules with fixed torsion and bend angles. Polymer Science Series A 53(8), 733–743 (Aug 2011).

Glagolev, M.K., Vasilevskaya, V.V.: Coarse-grained simulation of molecular ordering in polylactic blends under uniaxial strain. Polymer 190, 122232 (Mar 2020).

Glagolev, M.K., Vasilevskaya, V.V., Khokhlov, A.R.: Effect of Induced Self-Organization in Mixtures of Amphiphilic Macromolecules with Different Stiffness. Macromolecules 48(11), 3767–3774 (Jun 2015).

Glagolev, M.K., Vasilevskaya, V.V., Khokhlov, A.R.: Induced liquid-crystalline ordering in solutions of stiff and flexible amphiphilic macromolecules: Effect of mixture composition. The Journal of Chemical Physics 145(4), 044904 (Jul 2016).

Glagolev, M.K., Vasilevskaya, V.V., Khokhlov, A.R.: Domains in mixtures of amphiphilic macromolecules with different stiffness of backbone. Polymer 125, 234–240 (Sep 2017).

Glagolev, M. K., Vasilevskaya, V.V., Khokhlov, A.R.: Self-organization of amphiphilic macromolecules with local helix structure in concentrated solutions. The Journal of Chemical Physics 137(8), 084901 (Aug 2012).

Glova, A.D., Melnikova, S.D., Mercurieva, A.A., et al.: Grafting-Induced Structural Ordering of Lactide Chains. Polymers 11(12), 2056 (Dec 2019).

Grason, G.M.: Chirality Transfer in Block Copolymer Melts: Emerging Concepts. ACS Macro Letters 4(5), 526–532 (May 2015).

Grason, G.M.: Chiral and achiral mechanisms of self-limiting assembly of twisted bundles. Soft Matter 16(4), 1102–1116 (2020).

Grosberg, A.Y.: Theory of the cholesteric mesophase in a solution of chiral macromolecules. Soviet Physics Doklady 25, 638 (1980)

Hagberg, A.A., Schult, D.A., Swart, P.J.: Exploring Network Structure, Dynamics, and Function using NetworkX. In: Varoquaux, G., Vaught, T., Millman, J. (eds.) Proceedings of the 7th Python in Science Conference. pp. 11–15. Pasadena, CA, USA (2008)

Hajduk, D.A., Harper, P.E., Gruner, S.M., et al.: The Gyroid: A New Equilibrium Morphology in Weakly Segregated Diblock Copolymers. Macromolecules 27(15), 4063–4075 (Jul 1994).

Harris, C.R., Millman, K.J., van der Walt, S.J., et al.: Array programming with NumPy. Nature 585(7825), 357–362 (Sep 2020).

Ho, R.M., Li, M.C., Lin, S.C., et al.: Transfer of Chirality from Molecule to Phase in Self-Assembled Chiral Block Copolymers. Journal of the American Chemical Society 134(26), 10974–10986 (Jul 2012).

Humbert, M.T., Zhang, Y., Maginn, E.J.: PyLAT: Python LAMMPS Analysis Tools. Journal of Chemical Information and Modeling 59(4), 1301–1305 (Apr 2019).

Humphrey, W., Dalke, A., Schulten, K.: VMD: Visual molecular dynamics. Journal of Molecular Graphics 14(1), 33–38 (Feb 1996).

Hunter, J.D.: Matplotlib: A 2D Graphics Environment. Computing in Science & Engineering 9(3), 90–95 (2007).

Ji, X.Y., Zhao, M.Q., Wei, F., Feng, X.Q.: Spontaneous formation of double helical structure due to interfacial adhesion. Applied Physics Letters 100(26), 263104 (Jun 2012).

Kornyshev, A.A., Lee, D.J., Leikin, S., Wynveen, A.: Structure and interactions of biological helices. Reviews of Modern Physics 79(3), 943–996 (Aug 2007).

Lazzari, M., Liu, G., Lecommandoux, S. (eds.): Block copolymers in nanoscience. Wiley-VCH; John Wiley [distributor], Weinheim: Chichester (2006), oCLC: ocm69486595

Leibler, L.: Theory of Microphase Separation in Block Copolymers. Macromolecules 13(6), 1602–1617 (Nov 1980).

Li, M.C., Ousaka, N., Wang, H.F., et al.: Chirality Control and Its Memory at Microphase-Separated Interface of Self-Assembled Chiral Block Copolymers for Nanostructured Chiral Materials. ACS Macro Letters 6(9), 980–986 (Sep 2017).

McGibbon, R., Beauchamp, K., Harrigan, M., et al.: MDTraj: A Modern Open Library for the Analysis of Molecular Dynamics Trajectories. Biophysical Journal 109(8), 1528–1532 (Oct 2015).

Michaud-Agrawal, N., Denning, E.J., Woolf, T.B., Beckstein, O.: MDAnalysis: A toolkit for the analysis of molecular dynamics simulations. Journal of Computational Chemistry 32(10), 2319–2327 (Jul 2011).

Olsen, B., Segalman, R.: Self-assembly of rod-coil block copolymers. Materials Science and Engineering: R: Reports 62(2), 37–66 (Jul 2008).

Olsen, B.D., Segalman, R.A.: Nonlamellar Phases in Asymmetric Rod-Coil Block Copolymers at Increased Segregation Strengths. Macromolecules 40(19), 6922–6929 (Sep 2007).

Olsen, K., Bohr, J.: The generic geometry of helices and their close-packed structures. Theoretical Chemistry Accounts 125(3-6), 207–215 (Mar 2010).

Osipov, M.A., Gorkunov, M.V., Berezkin, A.V., et al.: Molecular theory of the tilting transition and computer simulations of the tilted lamellar phase of rod-coil diblock copolymers. The Journal of Chemical Physics 152(18), 184906 (May 2020).

Paavilainen, S., Rg, T., Vattulainen, I.: Analysis of Twisting of Cellulose Nanofibrils in Atomistic Molecular Dynamics Simulations. The Journal of Physical Chemistry B 115(14), 3747–3755 (Apr 2011).

Peacock, A., Stuckey, J., Pecoraro, V.: Switching the chirality of the metal environment alters the coordination mode in designed peptides. Angewandte Chemie International Edition 48(40), 7371–7374 (2009).

Pezoa, F., Reutter, J.L., Suarez, F., et al.: Foundations of JSON Schema. In: Proceedings of the 25th International Conference on World Wide Web. pp. 263–273. International World Wide Web Conferences Steering Committee, Montral, Qubec, Canada (Apr 2016).

Ruokolainen, J., Mkinen, R., Torkkeli, M., et al.: Switching Supramolecular Polymeric Materials with Multiple Length Scales. Science 280(5363), 557–560 (Apr 1998).

Rhle, V., Junghans, C., Lukyanov, A., et al.: Versatile Object-Oriented Toolkit for Coarse-Graining Applications. Journal of Chemical Theory and Computation 5(12), 3211–3223 (Dec 2009).

Straley, J.P.: Theory of piezoelectricity in nematic liquid crystals, and of the cholesteric ordering. Physical Review A 14(5), 1835–1841 (Nov 1976).

Tarjan, R.: Depth-First Search and Linear Graph Algorithms. SIAM Journal on Computing 1(2), 146–160 (Jun 1972).

Thompson, A.P., Aktulga, H.M., Berger, R., et al.: LAMMPS – a flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales. Computer Physics Communications 271, 108171 (Feb 2022).

Van Rossum, Guido, Drake, Fred L.: Python 3 Reference Manual. CreateSpace, Scotts Valley, CA

Virtanen, P., Gommers, R., Oliphant, T.E., et al.: SciPy 1.0: fundamental algorithms for scientific computing in Python. Nature Methods 17(3), 261–272 (Mar 2020).

Wang, H.F., Yang, K.C., Hsu, W.C., et al.: Generalizing the effects of chirality on block copolymer assembly. Proceedings of the National Academy of Sciences 116(10), 4080–4089 (Mar 2019).

Yang, Y., Meyer, R.B., Hagan, M.F.: Self-Limited Self-Assembly of Chiral Filaments. Physical Review Letters 104(25), 258102 (Jun 2010).

Yesylevskyy, S.O.: Pteros 2.0: Evolution of the fast parallel molecular analysis library for C++ and python. Journal of Computational Chemistry 36(19), 1480–1488 (Jul 2015).

Zhao, Y., Rothrl, J., Besenius, P., et al.: Can Polymer Helicity Affect Topological Chirality of Polymer Knots? ACS Macro Letters 12(2), 234–240 (Feb 2023).

Zhou, H.b., Wang, L.: Chaos in Biomolecular Dynamics. The Journal of Physical Chemistry 100(20), 8101–8105 (Jan 1996).

Zielinski, K., Sekula, B., Bujacz, A., Szymczak, I.: Structural investigations of stereoselective profen binding by equine and leporine serum albumins. Chirality 32(3), 334–344 (2020).




How to Cite

Glagolev, M. K., Glagoleva, A. A., & Vasilevskaya, V. (2024). MOUSE2: Molecular Ordering Utilities for Simulations, Edition 2. Supercomputing Frontiers and Innovations, 10(3), 73–87.